In training phase, we hold \(10\%\)  of the data as testing set and train on the remaining samples. We encode text instructions using Bert embedding [1]} separately on each word and generate word embeddings of length \(H=768\) . We use 8 as GRU hidden sizes. We perform optimization using Adam with \(1e-4\)  learning rate for 10 epochs. See the following section for training results.
